Salary guide
| Measure | Annual pay (USD) |
|---|---|
| 25th percentile | $187,000 |
| Median | $223,000 |
| 75th percentile | $269,000 |
| Lowest listing | $80,000 |
| Highest listing | $1,300,000 |
| Listings counted | 2,652 |
| Level | Listings | Median pay |
|---|---|---|
| Mid-level | 50 | $250,000 |
| Senior | 941 | $205,000 |
| Lead | 29 | $190,000 |
| Company | Open listings | Median pay |
|---|---|---|
| NVIDIA | 189 | $204,000 |
| OpenAI | 128 | $356,000 |
| Roblox | 108 | $269,000 |
| Anduril Industries | 84 | $222,000 |
| Anthropic | 74 | $403,000 |
| Databricks | 63 | $216,000 |
| Snowflake | 58 | $244,000 |
| Nuro | 46 | $291,000 |
| Country | Currency | Listings | Median pay | Middle half |
|---|---|---|---|---|
| United States | USD | 2,432 | $223,000 | $189,000 to $269,000 |
| Canada | USD | 66 | $225,000 | $197,000 to $255,000 |
| United Kingdom | USD | 6 | $219,000 | $184,000 to $231,000 |
When someone calls an airline, texts a retailer, or opens their bank's app and talks to a Sierra agent, our systems carry that conversation. Phone calls, SMS, WhatsApp, email, and the chat inside our customers' apps all run through this team.
Reporting & Experimentation: Build a system for analyzing and visualizing millions of data points about agent performance. Enable agent developers to run A/B test their agents to make data-driven decisions about agent behavior.
Simulation & Benchmarking: How can we craft a simulation platform to test AI agents against every real-world scenario imaginable? Content Management: How do we create intuitive, no-code tools that allow anyone to guide and test AI agents?
Build the core systems that power agents. You’ll work on the Agent SDK — the orchestration engine, runtime, and primitives that define how agents reason, take actions, and interact with users and systems. Design the agentic loop.
The Inference team builds the systems that make those models fast, reliable, and efficient at scale. As a Software Engineer on Inference, you’ll help define Sierra’s inference architecture across both self-hosted models and third-party inference providers.
Agent Architecture: What primitives do we need to build agents that are steerable and verifiable, but also conversational and empathetic? How do we future-proof this as LLMs evolve? Retrieval: How do we ground answers in a customer’s knowledge base?
As a Software Engineer, Infrastructure at Sierra, you will be responsible for designing, building, and maintaining the core systems that make our AI platform possible.
Our work spans several security domains. You’ll go deep where your strengths and interests are strongest, with opportunities to explore new areas alongside the team. Build the Foundations of Trust.
Build Sierra’s platform. You will work on the platform primitives that power how agents are built, orchestrated, and deployed. Invent the foundations of agent development.
Design and deliver production-grade AI agents : You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth.
Design and deliver production-grade AI agents : You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth.
Sierra · 1mo ago
Design and deliver production-grade AI agents : You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth.
Design and deliver production-grade AI agents : You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth.
Design and build production-grade AI agents for government institutions at the Federal and state level. Partner closely with industry leadership to build our public sector team, including our capture motion, market strategy, and product components to scale quickly.
Design and deliver production-grade AI agents : You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth.
Design and deliver production-grade AI agents for healthcare: You'll build and ship highly performant, reliable, and empathetic AI agents that handle sensitive patient and member interactions.
Sierra · 4mo ago
Design and deliver production-grade AI agents : You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth.
Design and deliver production-grade AI agents : You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth.
Lead the engineering team responsible for the App Promotion objective and App Install Optimization, owning delivery from beta through GA.
At Zoox, you will collaborate with a team of world-class engineers with diverse backgrounds in areas such as AI, robotics, mechatronics, planning, control, localization, computer vision, rendering, simulation, distributed computing, design, and automated testing.
As a Staff / Senior Staff Technical Lead on Onboard Performance, you will help define and build the high-performance, highly reliable foundation of the Nuro Driver.
The Context Engine is ServiceNow’s platform for connecting enterprise data, knowledge graphs, and AI workloads into a single, governed context layer.
OpenAI · 21d ago
The Privacy Engineering team builds secure, reliable systems that help OpenAI meet its legal obligations while protecting user data. We partner closely with Legal and engineering teams across OpenAI to support lawful data access requests and other critical legal workflows.
Dots is building personal AI agents that help people make progress on their goals, including when they are away from ChatGPT. These agents can learn preferences, maintain context, work across applications, and use cloud computers to carry out tasks.
We build AI systems that support patients, clinicians, and healthcare organizations while setting a high standard for deploying AI responsibly in a high-stakes domain. We serve health care systems, insurance companies, and the broad range of healthcare IT companies.
The Statsig team within OpenAI owns the experimentation, rollout, dynamic configuration, and analytics infrastructure that sits on the launch path for OpenAI products.
The Consumer Products team at OpenAI builds end-to-end hardware and software systems that bring AI into the physical world.
We build foundational platform software that enables reliable, secure, and performant products. The team works across system layers and partners closely with adjacent engineering groups to deliver robust capabilities from concept through launch.
The Connectivity Software Engineering team is responsible for enabling seamless, secure, and high-performance wireless connectivity across OpenAI’s products.
A key part of achieving that mission is training models that deeply understand and reflect human preferences — the Human Data team is at the heart of that effort. The Human Data engineering team creates the systems that enable scalable, high-quality human feedback.
The Integrity team builds the systems that protect OpenAI’s products, users, and ecosystem from abuse. We work across product engineering, infrastructure, safety, and operations to detect and prevent harmful, fraudulent, deceptive, and adversarial activity at global scale.
The GPT Infrastructure team builds systems that turn advances in model inference and optimization into reliable production capabilities.
The Scaling team is responsible for the architectural and engineering backbone of OpenAI’s infrastructure. We design and deliver advanced systems that support the deployment and operation of cutting-edge AI models.
Customer education helps customers and partners build the practical skills and confidence to use AI and OpenAI products safely and effectively.
The Agent Platform team at OpenAI builds the production systems that bring useful AI agents to users around the world. We provide the platform that enables agents to execute code, use tools, and interact with software reliably and securely at scale.
Enterprise Controls & Console is part of Enterprise Engineering. We build the permissions, governance, and administration capabilities that help organizations use and deploy ChatGPT, Codex, and OpenAI products with confidence.
We focus on specific use cases such as customer support, sales, and insurance claims, helping organizations put agents to work in production.
The Private Computing team works across product, engineering, security, and safety to build advanced privacy products and infrastructure at OpenAI.
OpenAI · 5mo ago
Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models.
OpenAI · 6mo ago
We’re hiring a Developer Productivity engineer to support OpenAI’s Inference Runtime teams. These teams own the systems responsible for serving models reliably, efficiently, and safely across Codex, ChatGPT, API, and internal research workloads.
The Codex Core Agent team builds the kernel of Codex. We own making the agent better, accelerating research, and making those improvements real in production for our users.
Codex is OpenAI’s coding agent, helping developers write, review, and debug software. The broader Codex group combines research, engineering, design, and product to advance what AI agents can do.
Design, build, and operate backend services that enforce policy-driven data access, lifecycle controls, and privacy protections. Develop distributed authorization and identity-aware enforcement mechanisms integrated directly into data services and control planes.
At OpenAI, we’re building safe and beneficial artificial general intelligence. We deploy our models through ChatGPT, our APIs, and other cutting-edge products. Behind the scenes, making these systems fast, reliable, and cost-efficient requires world-class infrastructure.
The Core Services team is responsible for building and managing foundational services.
The Agent Infrastructure team at OpenAI is responsible for building systems that enable training and deployment of highly useful AI agents, both internally and for the world.
The Storage Infrastructure team builds and operates the storage foundation behind OpenAI’s most demanding workloads. We work directly with research to design storage systems for rapidly evolving experiments, while also powering production at scale.
The Safety Systems org is responsible for various safety work to ensure our best models can be safely deployed to the real world to benefit the society and is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a…
The Safety Systems team is dedicated to ensuring the safety, robustness, and reliability of AI models and their deployment in the real world. Learn more about OpenAI’s approach to safety.
The median Software Engineer salary in our $100k+ listings is $223,000 a year, based on 2,652 live USD listings. The middle half of listings pays $187,000 to $269,000. These figures cover only listings that publish a salary of $100k+ or more, so they sit above pay for Software Engineer roles overall.
Individual $100k+ Software Engineer listings range from $80,000 to $1,300,000 a year. The 25th percentile of listing midpoints is $187,000 and the 75th percentile is $269,000.
Median pay by level in our $100k+ listings: mid-level $250,000 (50 listings), senior $205,000 (941 listings), lead $190,000 (29 listings). Levels with fewer than 5 listings are left out.
The companies with the most open $100k+ Software Engineer listings are NVIDIA (189 listings, median $204,000), OpenAI (128 listings, median $356,000), Roblox (108 listings, median $269,000), Anduril Industries (84 listings, median $222,000) and Anthropic (74 listings, median $403,000).
The figures come from the salary ranges employers publish in their own job listings, collected from company career pages and applicant-tracking systems. Each listing counts once, at the midpoint of its range. Only USD listings go into the headline figures, and listings that are closed or stale are removed. The data was last refreshed on November 12, 2026.
Yes. Each listing is tagged remote, hybrid or on-site, and remote roles carry a region (US only, EMEA, APAC or global), so you can filter the live job list to the arrangement you want.
United States
Canada
United Kingdom
